Jędrzej Orbik — accepted AI-conference papers

2025

Demonstrating REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly

Daniel Sliwowski, Shail Jadav, Sergej Stanovcic, Jędrzej Orbik, Johannes Heidersberger, Dongheui Lee

RSS 2025poster

Robotic manipulation remains a core challenge in robotics, particularly for contact-rich tasks such as industrial assembly and disassembly. Existing datasets have significantly advanced learning in manipulation but are primarily focused on simpler tasks like object rearrangement, falling short of ca…

Cited by 3 PDF ↗Scholar ↗

2022

Don’t Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning

Homer Rich Walke, Jonathan Heewon Yang, Albert Yu, Aviral Kumar, Jędrzej Orbik, Avi Singh +1

CoRL 2022poster

Reinforcement learning (RL) algorithms hold the promise of enabling autonomous skill acquisition for robotic systems. However, in practice, real-world robotic RL typically requires time consuming data collection and frequent human intervention to reset the environment. Moreover, robotic policies lea…

Cited by 48 Source ↗Scholar ↗

2021

Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation

Charles Sun, Jędrzej Orbik, Coline Manon Devin, Brian H Yang, Abhishek Gupta, Glen Berseth +1

CoRL 2021poster

In this paper, we study how robots can autonomously learn skills that require a combination of navigation and grasping. Learning robotic skills in the real world remains challenging without large scale data collection and supervision. Our aim is to devise a robotic reinforcement learning system for…

Cited by 58 Source ↗Scholar ↗